Estimation of breeding probability can make monitoring data more revealing: a case study of amphibians

Monitoring programs serve to detect trends in the distribution and abundance of species. To do so, monitoring programs often use static state variables. Dynamic state variables that describe population dynamics might be more valuable because they allow for a mechanistic understanding of the processes that lead to population trends. We fit multistate occupancy models to data from a country-wide multispecies amphibian occupancy monitoring program and estimated occupancy and breeding probabilities. If breeding probabilities are determinants of occupancy dynamics, then they may serve in monitoring programs as state variables that describe dynamic processes. The results showed that breeding probabilities were low and that a large proportion of the populations had to be considered to be non-breeding populations (i.e., populations where adults are present but no breeding occurs). For some species, the majority of populations were non-breeding populations. We found that non-breeding populations have lower persistence probabilities than populations where breeding occurs. Breeding probabilities may thus explain trends in occupancy but they might also explain other ecological phenomena, such as the success of invasive species, which had high breeding probabilities. Signs of breeding, i.e., the presence of eggs and larvae, were often hard to detect. Importantly, non-breeding populations also had low detection probabilities, perhaps because they had lower abundances. We suggest that monitoring programs should invest more in the detection of life history stages indicative of breeding, and also into the detection of non-breeding populations. We conclude that breeding probability should be used as a state variable in monitoring programs because it can lead to deeper insights into the processes driving occupancy dynamics.

Performance of visual vs. software-assisted photo-identification in mark-recapture studies: a case study examining different life stages of the Pacific Horned Frog (Ceratophrys stolzmanni)

The use of individual phenotypic features as non-invasive marks through photo-identification (photo-ID) has many advantages for individual-based field studies. However, since error rates vary between species, matching techniques, and image qualities, it is important to assess error rates to evaluate the reliability of photo-ID. We tested the performance of this method in the Pacific Horned Frog, Ceratophrys stolzmanni, a threatened anuran with a variable dorsal coloration. We compared the effectiveness of visual (i.e. human recognition) versus software-assisted recognition techniques (Wild-ID and APHIS), and assessed the potential applicability of these techniques to identify post-metamorphic individuals (froglets). The three techniques differed in their performance. The visual technique was the only one to produce type I errors between pairs of images (i.e. matching images which are not true matching pairs), however it also produced fewer type II errors (i.e. not identifying true matching pairs of images) than the software-assisted techniques. For froglets, we found that similarity scores calculated by photo-ID software did not differ significantly between groups of froglets and older individuals, supporting the idea that colour patterns in this species remain stable after metamorphosis. The lack of type I errors and the substantial reduction in required time achieved through the use of software, make software-assisted techniques (particularly Wild-ID) a valid and convenient matching technique for C. stolzmanni. We propose that photo-ID can also be applied to froglets of this species, since the pattern at this stage appears to be as variable as in adults and maintained through life.

Quantifying climate sensitivity and climate-driven change in North American amphibian communities

Changing climate will impact species' ranges only when environmental variability directly impacts the demography of local populations. However, measurement of demographic responses to climate change has largely been limited to single species and locations. Here we show that amphibian communities are responsive to climatic variability, using >500,000 time-series observations for 81 species across 86 North American study areas. The effect of climate on local colonization and persistence probabilities varies among eco-regions and depends on local climate, species life-histories, and taxonomic classification. We found that local species richness is most sensitive to changes in water availability during breeding and changes in winter conditions. Based on the relationships we measure, recent changes in climate cannot explain why local species richness of North American amphibians has rapidly declined. However, changing climate does explain why some populations are declining faster than others. Our results provide important insights into how amphibians respond to climate and a general framework for measuring climate impacts on species richness.

Error rates and variation between observers are reduced with the use of photographic matching software for capture-recapture studies

Photographic capture-mark-recapture (CMR) permits individual recognition whilst avoiding many of the concerns involved with marking animals. However, the construction of capture histories from photographs is a time-consuming process. Furthermore, matching accuracy is determined based on subjective judgements of the person carrying out the matching, which can lead to errors in the resulting datasets – particularly in long-term projects where multiple observers match images. We asked 63 volunteers to carry out two photographic-matching exercises using a database of known individuals of the yellow-bellied toad (Bombina variegata). From these exercises, we quantified the matching accuracy of volunteers in terms of false-acceptance and false-rejection rates. Not only were error rates greatly reduced with the use of photographic-matching software, but variation in error rates among volunteers was also lowered. Furthermore, the use of matching software led to substantial increases in matching speeds and an 87% reduction in the false-rejection rate. As even small error rates have the potential to bias CMR analyses, these results suggest that computer software could substantially reduce errors in CMR datasets. The time-savings and reduction in variance among observers suggest that such methods could be particularly beneficial in long-term CMR projects where a large number of images may be matched by multiple observers.

Quantifying population declines based on presence-only records for red-list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy-modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red-list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence-only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.